Computational Tools
We work closely with collaborators specializing in Biostatistics and Epidemiology to develop research involving the computational analysis of complex relationships between genes and their environment as well as basic biolanalysisogical and quantitative sciences. The lab is especially interested in using these approaches to explore the molecular archives of past-life experiences and use them as early predictors of an individual's risk of future disease. Our team is developing and applying novel approaches for genome-scale epigenomic analysis. Recent activity has included creating algorithms for bioinformatic and biostatistical analysis of 850K Methylation BeadChip data, as well as Bayesian kernel machine regression (BKMR) which is used to study the health effect of a mixture of exposures.